International Conference Proceeding
2026
Tierlog: AI-Driven Feedback Prioritization and Version Aware E-Logbook for Thesis Supervision (Submitted to ICIMTech 2026)
Project Summary
This scientific study proposes an artificial intelligence-based thesis supervision system architecture to address inefficiencies in progress tracking and asynchronous communication between students and their advisors. By combining Natural Language Processing (NLP) for prioritizing feedback and a semantic version-control system for logbook entries, this platform minimizes missed revisions and measurably accelerates the academic supervision cycle.
Core Capabilities
Technical Challenges & Solutions
The main challenge lies in designing an objective feedback scoring model that accounts for the dynamic nature of thesis revision without introducing priority bias. The key takeaway is the importance of validating empirical data and evaluating usability from the perspectives of both faculty and students so that the system can be easily adopted within academic institutions.
Tech Stack
research-paper
Project Details
Year
2026
Category
International Conference Proceeding
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